Analysis of Labour Participation Behaviour of Korean Women with Dynamic Probit and Conditional Logit
Myoung-jae Lee and
Yoon‐Hee Tae
Oxford Bulletin of Economics and Statistics, 2005, vol. 67, issue 1, 71-91
Abstract:
We analyse the dynamic labour participation behaviour of Korean women. State dependence under unobserved heterogeneity is considered, where the heterogeneity may be unrelated, pseudo‐related, or arbitrarily related to regressors. Three minor methodological contributions are made: interaction terms with lagged response are allowed in dynamic conditional logit; a three‐stage algorithm for dynamic probit is proposed; and treating the initial response as fixed is shown to be ill‐advised. The state dependence is about 0.6 × SD(error), higher for the married or junior college‐educated, and lower for women in their twenties and thirties. While education increases participation, college education has negative effects for women in their forties or above. Marriage has a high negative short‐term effect but a positive long‐term effect.
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)
Downloads: (external link)
https://doi.org/10.1111/j.1468-0084.2005.00110.x
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:obuest:v:67:y:2005:i:1:p:71-91
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0305-9049
Access Statistics for this article
Oxford Bulletin of Economics and Statistics is currently edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple
More articles in Oxford Bulletin of Economics and Statistics from Department of Economics, University of Oxford Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().